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    Kruthikk Nm

Federated searches have transformed compliance audits but user access and trials still need improvement

  • April 02, 2026
  • Review provided by PeerSpot

What is our primary use case?

Query.ai serves as a security platform that provides expanded data visibility without centralizing. I use it for query federated search, Query.ai for Splunk, and for AI agents and data security pipelines. My background in IT pipelines and API integration enables me to use Query.ai for building AI agents. I can also use it for Splunk and federated search. Instead of building custom data pipelines to centralize, which is the kind of engineering work I have done with other platforms such as ClickHouse and Pi, Query.ai lets me federate search across all sources without moving data.

What is most valuable?

The best feature that Query.ai offers is that I need not move into multiple databases. For example, I can use ClickHouse and Pi in one federated search without moving my data, resulting in no pipelines, no duplication, and no ingestion cost inflation. For someone building data pipelines and who knows how painful data engineering overhead gets, this federated search without moving into multiple databases really helps me. I do not have to move into multiple databases or multiple platforms, and with just one federated search, I can go through all those databases within one direct application without causing any pipelines and duplication.

Query.ai has positively impacted my organization with its ability to audit data flow and assist in compliance with HIPAA regulations. Since I work in a privacy-sensitive market, I use Query.ai to perform audit prep, which was entirely manual, error-prone, and resource-intensive before. With Query.ai, I can automate it, and HIPAA breach investigation response times, which were slow earlier, have sped up. Query.ai helps reduce costs and improve security in my organization, though I do not have the actual numbers, but the impact was significant.

What needs improvement?

A more user-friendly interface can add more users to the platform. Additionally, there could be a trial phase or a free trial version of Query.ai. I would like to use a free version without adding my credit card details or any payment details. If I could compare other audit trails or other audit software with Query.ai in real-time, that would be helpful.

For how long have I used the solution?

I have been using Query.ai for about six months.

What other advice do I have?

Query.ai performs well, but there are other software options that do auditing a little better. Overall, Query.ai is quite useful for auditing and database migration and data pipelines. Query.ai is a useful platform or software, especially in my domain, which is healthcare. The combination of communication data plus Query.ai's feature search creates a compelling story, particularly for multi-location practices where data sprawl is the norm and not an exception, making Query.ai useful in these situations. I would rate this review seven out of ten.


    reviewer2813226

Automation has transformed reporting workflows and saves days by streamlining data lake projects

  • April 01, 2026
  • Review provided by PeerSpot

What is our primary use case?

My main use case for Query.ai is connecting to data lakes and data marts using Amazon S3. I have been connecting my data to Query.ai data lakes and data marts while doing some transformation, creating reports, and sharing them with my clients. A reporting project is what I recently completed.

What is most valuable?

Query.ai is very simple, which makes it excellent for beginners to start with all of these features. The interface itself and the UI are what make Query.ai simple for beginners. I can see what all features are available in Query.ai, the different features, how they can be useful, how they are implemented, and the description of all processes. It is unique and simple.

Query.ai has had a positive impact on my organization. I have been introducing this to my colleagues and they were very happy with this application.

Time saving and accuracy are the main benefits. In my data mart and data lakes project, Query.ai has been very useful. All transformations were automated, which had a huge impact on our entire project. Everything is automated using Query.ai and we do not need to think about whether it is running or not. It will take care of itself.

What needs improvement?

I think integrating some LLM would be good because nowadays AI has a very huge impact. Additionally, I think it would be good if you add Amazon QuickSight for the reporting functionality.

For how long have I used the solution?

I have been using Query.ai for the last one year.

Which solution did I use previously and why did I switch?

Query.ai was my first solution.

What was our ROI?

The time saving is a big thing. For example, work that needs to be completed in five days is completed in just one or two days, which is a big deal.

What's my experience with pricing, setup cost, and licensing?

My experience with pricing, setup cost, and licensing was good. I felt the pricing is somewhat higher.

Which other solutions did I evaluate?

Query.ai came into my picture and I analyzed it. I think this is a good option, so I went with this.

What other advice do I have?

Query.ai is very useful for my entire project and I like it. I will be sharing this with my colleagues and also with my friends who are working in other companies. I mention every time that Query.ai is really useful in real life. I gave this review a rating of eight out of ten.


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